As a Gates Research Scientist, you will work on identifying noise processes through precise error benchmarking and use these results to identify new gate design and architecture parameters. You will implement improved error-metrology circuits and cross-validate them with physical models from the theory team. You will also be responsible for conducting detailed circuit analysis and simulations, and defining hardware requirements of new gate designs for forward-looking architectures.
In this role, you will collaborate with other research scientists, hardware engineers, and software engineers to make high-performance quantum computing a reality.
The full potential of quantum computing will be unlocked with a large-scale computer capable of complex, error-corrected computations. Google Quantum AI's mission is to build this computer and unlock solutions to classically intractable problems. Our roadmap is focused on advancing the capabilities of quantum computing and enabling meaningful applications.
The US base salary range for this full-time position is $147,000-$211,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.
Responsibilities
- Characterize and identify limiting error mechanisms in quantum logic gates.
- Partner with the theory team to build and verify physics models for noise and error processes in quantum logic gates.
- Execute detailed superconducting circuit analysis, analyze design parameters and build hardware system specifications for forward-look architectures.
- Develop software infrastructure and tools for wider team use.
Qualifications
Minimum qualifications:
- PhD in Physics, Applied Physics, or Electrical Engineering (or equivalent technical field) or equivalent practical experience.
- Experience collecting and analyzing data in an experimental setting.
- Experience with programming and statistical analysis of datasets.
- Experience with techniques to characterize and calibrate hardware performance.
Preferred qualifications:
- 2 years of coding experience in Python.
- Experience in circuit theory.
- Experience in Superconducting Quantum Computing.
- Experience in circuit analysis and modeling of multi-qubit quantum platforms.